The Impact of Industry 4.0 on Employees—Insights from Australia

Ejsmont, Krzysztof

doi:10.3390/su13063095

Cited by 31 publications

(17 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…However, psychological and behavioral barriers have not been appropriately addressed in the literature [ 19 ]. Several studies are limited to the technological side, insufficiently considering social aspects [ 20 , 21 ]. Hence, there is a lack of studies in the latest literature that identify and create causal relationships among the psychological barriers to adopting the i4.0 phenomenon [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

Developing an interplay among the psychological barriers for the adoption of industry 4.0 phenomenon

et al. 2021

View full text Add to dashboard Cite

This research aims to identify, rank, and create an interplay among the psychological barriers to adopting Industry 4.0 technologies in the manufacturing sector. A comprehensive literature review tracked by a discussion with industry and academic experts recognized 20 barriers. Based on three widely acclaimed statistical techniques, hybrid AHP-TOPSIS (Analytical Hierarchy Process-Technique for Order Performance by Similarity to Ideal Solution) and ISM (Interpretative Structural Modeling), critical psychological barriers have been investigated. A group of 8 experts from industry and academia with at least 10 years of experience was consulted for AHP and ISM techniques. Whereas TOPSIS was conducted by 443 operational-level users, including managers and supervisors of different functional areas of the manufacturing industry located in Pakistan. The findings reveal that ‘Fear of job losses’, ‘Fear of data loss/Risk of security breaches, ‘Lack of advanced & continued education of employees’ and ‘Lack of standards and reference architecture’, with highest importance weights, emerged as the most prominent psychological barriers in developing economies. Then the interrelations among these barriers resulted in a four-layered structural model. The driver barriers identified in the final model advocate that development in ‘advanced & continued education of employees’, ‘standards & reference architecture’ and ‘minimization of fear of job & data loss’ can expedite the adoption of industry 4.0 (i4.0) technologies. The study uniquely develops hierarchical relationships among the psychological barriers for adopting i4.0 in the manufacturing context using AHP-TOPSIS and ISM techniques. The study would be valuable for practitioners, decision-makers and companies that wish to focus their efforts and resources on removing the most critical barriers and challenges for the seamless implementation of Industry 4.0.

show abstract

Section: Introductionmentioning

confidence: 99%

Developing an interplay among the psychological barriers for the adoption of industry 4.0 phenomenon

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Solving the PSR optimization problem has great relevance, due to the changes in the forms of work that are currently taking place [1,[7][8][9]63]. Algorithmic management [2,[64][65][66], which assigns tasks and evaluates workers using data-driven systems, has proven to be efficient.…”

Section: Discussionmentioning

confidence: 99%

Optimization Method to Address Psychosocial Risks through Adaptation of the Multidimensional Knapsack Problem

Eraña-Díaz¹,

Cruz-Chávez²,

Juárez-Pérez

et al. 2021

Mathematics

View full text Add to dashboard Cite

This paper presents a methodological scheme to obtain the maximum benefit in occupational health by attending to psychosocial risk factors in a company. This scheme is based on selecting an optimal subset of psychosocial risk factors, considering the departments’ budget in a company as problem constraints. This methodology can be summarized in three steps: First, psychosocial risk factors in the company are identified and weighted, applying several instruments recommended by business regulations. Next, a mathematical model is built using the identified psychosocial risk factors information and the company budget for risk factors attention. This model represents the psychosocial risk optimization problem as a Multidimensional Knapsack Problem (MKP). Finally, since Multidimensional Knapsack Problem is NP-hard, one simulated annealing algorithm is applied to find a near-optimal subset of factors maximizing the psychosocial risk care level. This subset is according to the budgets assigned for each of the company’s departments. The proposed methodology is detailed using a case of study, and thirty instances of the Multidimensional Knapsack Problem are tested, and the results are interpreted under psychosocial risk problems to evaluate the simulated annealing algorithm’s performance (efficiency and efficacy) in solving these optimization problems. This evaluation shows that the proposed methodology can be used for the attention of psychosocial risk factors in real companies’ cases.

show abstract

“…Technologically leveraged transparency, real-time tracking and data-based decision-making affect the workforce and invite resistance from highly experienced people. Ejsmont (2021) highlighted the management of human resources as the biggest challenge in the robotic era. The change of mindset of the management, staff and workers will play a critical role.…”

Section: Literature Reviewmentioning

confidence: 99%

Development of an industry 4.0 transformability index for manufacturing systems

Kumar

Asjad

James³

et al. 2022

View full text Add to dashboard Cite

Purpose Evaluation of the extent of transformability of an existing system into an industry 4.0 (I4.0) compatible system is indispensable for both the technical and economic planning for implementing I4.0. This paper aims to propose a procedure to evaluate the transformability of an existing manufacturing system into an I4.0 system. Design/methodology/approach Six significant components of a manufacturing system and their five levels of modifications essential for the decision of transformation are identified. Based on expert opinion on facilitation and the impact of the transformation of one component on the transformation of others, a graph theory-based procedure for estimation of transformability index (TI) along with its relative and threshold values is proposed. Findings The paper introduced the concept of transformability into manufacturing systems. It proposed a simple procedure for calculating the ideal, relative and threshold value for TI to assess the suitability of the up-gradation of any manufacturing system into the I4.0 system. Research limitations/implications Though the proposed procedure is based on six system components and their five levels of facilitation, it is quite versatile and able to integrate new components and different facilitation levels according to system requirements for their impact analysis in the transformation process. It can be extended to other domains like services and health care. Further, it can be used to estimate and establish the transformability criteria of a factory/service unit/industry from its current state to any regime. Practical implications The proposed method for deducing the TI, relative transformability index (RTI) and their threshold values would be a handy tool for decision-makers to assess the upgrading suitability of the entire manufacturing system and its component for use in the new regime or scrapping. It would provide mathematical and scientific support to the transformability decisions by assessing the influence of transforming one component to others and the system. This study would pave the way for further explorations in the domain of transformability. Originality/value In the light of available literature and best of the author’s knowledge, this study is the first of its kind that has applied the concept of transformability of existing manufacturing systems toward I4.0 compatible systems and proposed a procedure to estimate TI, RTI and their threshold values.

show abstract

The Impact of Industry 4.0 on Employees—Insights from Australia

Cited by 31 publications

References 48 publications

Developing an interplay among the psychological barriers for the adoption of industry 4.0 phenomenon

Developing an interplay among the psychological barriers for the adoption of industry 4.0 phenomenon

Optimization Method to Address Psychosocial Risks through Adaptation of the Multidimensional Knapsack Problem

Development of an industry 4.0 transformability index for manufacturing systems

Contact Info

Product

Resources

About